[noitemsep,nolistsep]
BART For each claim, we use BART [1]} to generate a set of questions separated by a separation token [SEP]. This is a replication of the QABriefer model reported by [2]}.

SQuAD We train an answer-aware question generation model [3]} on the SQuAD dataset [4]}
without further fine-tuning on the QABriefs dataset. However, we use focal points instead of the answers. We extract the focal points using the method described in Section REF .

Varifocal We pretrain the model on SQuAD and fine-tune it on the QABriefs dataset. The models take tuples of the form \((c, f_i, q_i)\)  as input.

Varifocal+Meta We pretrain the model on SQuAD and fine-tune it on the QABriefs dataset with the metadata associated with each claim.

